...
首页> 外文期刊>Continental Shelf Research: A Companion Journal to Deep-Sea Research and Progress in Oceanography >A hybrid approach to transport processes in the Gulf of Naples: an application to phytoplankton and zooplankton population dynamics
【24h】

A hybrid approach to transport processes in the Gulf of Naples: an application to phytoplankton and zooplankton population dynamics

机译:那不勒斯湾运输过程的混合方法:在浮游植物和浮游动物种群动态中的应用

获取原文
获取原文并翻译 | 示例
           

摘要

A hybrid numerical approach was developed to study the dispersion of passive/reactive tracers in the Gulf of Naples (GON). To this end, an Eulerian and a Lagrangian scheme were implemented in the barotropic form of the Princeton Ocean Model (POM) and applied to the dispersion of zoo- and phytoplankton in the GON. The hybrid technique was first validated by comparing the tracer concentration patterns from the Eulerian model and maps of particle positions from the Lagrangian model. Excellent agreement in both spatial distribution and temporal evolution of these quantities was found between the two models. Second, the circulation in the GON was simulated using the POM model. While using simplified forcing fields, the simulated circulation patterns in the GON reproduce many observed features. These include the flushing of the GON waters typically occurring in spring and the formation of a close cyclonic gyre (trapping and homogenizing tracers in the GON) in autumn. The circulation patterns are strongly influenced by both the surface wind stresses and bathymetry and only "remotely" by the Tyrrhenian circulation. For the biological application, the spatial and temporal evolution of passive tracers (e.g., nutrients) was simulated using the Eulerian approach and that of the zoo- and phytoplankton using the Lagrangian approach. These populations were assumed to follow a prey-predator relationship and were studied using a grid resolution of 1.5 km. At these scales, the biological and physical processes (e.g., grazing, phyto- and zooplankton growth rate, mesoscale eddies, horizontal turbulent diffusion), influence plankton heterogeneity and patchiness. In particular, the model results show that phytoplankton variability have spatial and temporal scales similar than those of the carrying capacity (considered here as the effect of a limiting nutrient), yet bigger than the flow turbulence due to diffusion processes. The zooplankton population on the other hand develops on smaller scales due to its longer time taken to mature. The temporal evolution of the two populations shows that they follow a cyclical pattern which is smooth at time when the magnitude of the mean flow is much larger than the amplitude of the turbulent component of the ocean current and "noisy" at time when the turbulent component is larger than the mean flow. The high frequency oscillations are caused by the turbulence of the background ocean current through which the parcels move. A time lag of 20 days between phytoplankton and zooplankton concentrations was simulated, with the zooplankton temporal variability smaller than that of the phytoplankton. These results show that the hybrid Eulerian-Lagrangian technique here implemented is an appropriate tool to investigate the complex interactions between physical and biological dynamics. (c) 2005 Elsevier Ltd. All rights reserved.
机译:开发了一种混合数值方法来研究那不勒斯湾(GON)中被动/反应示踪剂的扩散。为此,以普林斯顿海洋模型(POM)的正压形式实施了欧拉和拉格朗日方案,并将其应用于GON中动植物和浮游植物的扩散。混合技术首先通过比较欧拉模型的示踪剂浓度模式和拉格朗日模型的颗粒位置图进行验证。在两个模型之间发现了这些数量的空间分布和时间演化的极佳一致性。其次,使用POM模型模拟了GON中的循环。在使用简化的强迫场时,GON中的模拟循环模式重现了许多观察到的特征。这些措施包括冲洗一般在春季发生的GON水,以及在秋季形成密闭的旋流回旋(在GON中捕获和均化示踪剂)。循环模式受表面风应力和测深法的强烈影响,而仅受到第勒尼安循环的“远程”影响。对于生物学应用,使用欧拉方法模拟了被动示踪剂(例如营养物)的时空演化,使用拉格朗日方法模拟了动植物和浮游植物的时空演化。假定这些种群遵循捕食者与捕食者的关系,并使用1.5 km的网格分辨率进行了研究。在这些尺度上,生物和物理过程(例如放牧,浮游植物和浮游动物的生长速度,中尺度涡旋,水平湍流扩散)会影响浮游生物的异质性和斑块。特别是,模型结果表明,浮游植物的可变性在空间和时间上的尺度与承载能力(在这里被认为是营养的限制)相似,但比由于扩散过程而产生的湍流更大。另一方面,由于浮游动物的成熟时间较长,因此它们的规模较小。这两个种群的时间演变表明,它们遵循周期性模式,当平均流量的大小远大于洋流湍流分量的幅度时,它们是平滑的;而当湍流分量时,则是“嘈杂”的。大于平均流量。高频振荡是由包裹移动通过的背景洋流的湍流引起的。模拟了浮游植物和浮游动物浓度之间的20天时滞,浮游动物的时间变异性小于浮游植物。这些结果表明,此处实施的混合欧拉-拉格朗日技术是研究物理和生物动力学之间复杂相互作用的合适工具。 (c)2005 Elsevier Ltd.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号